As more energy is extracted from the cochlea, it is continually buffered onto C DD, forcing its voltage, V DD, and as a result its stored energy, to rise. Since the EP voltage is low (typically between 70–100 mV), a boost converter is used to process the energy up to a higher voltage (typically between 0.8–1.0 V), which is directly dumped onto capacitor C DD. A figure of the EP harvesting system is shown in Fig. To validate the design, the transmitter is integrated into a system that harvests energy from the Endocochlear Potential (EP) - an electrochemical gradient found naturally in the inner-ear of mammals - which can only sustain energy extraction of approximately 1 nW. To achieve this, a low-complexity, single-stage direct-RF architecture is employed, featuring significant power gating and sizing optimizations for minimized leakage power. In order to enable next generation sensor nodes with near-zero-power for energy-autonomous operation in combination with energy harvesting, this paper presents a 2.4 GHz transmitter that is specifically optimized for standby power in the picowatt regime. As a result, the average power of such radios do not necessarily scale well down to ultra-low data rates. At such average data rates, leakage and standby power are not critical, and therefore not aggressively optimized. However, such architectures are typically demonstrated and optimized for efficient performance at data rates exceeding 100 kbps. Many recent publications in the area of energy-efficient RF circuits have described receivers, transmitters, and transceivers with excellent RF performance at efficiencies down to tens-to-hundreds of picojoules per bit. Thus, there is considerable interest in minimizing the power consumption of RF circuits in such sensing nodes. However, even under low path-loss constraints, RF circuits still often dominate the power consumption of sensor nodes. Thus, local base stations are typically employed in locations where energy is more abundant - a smartphone within a Body-Area Network (BAN), for example. In general, miniaturized sensing systems communicate their measured information wirelessly over a short distance (e.g., often only a few meters) in order to minimize the active-mode power of the constituent Radio Frequency (RF) Power Amplifier (PA). Thus, minimizing the standby-mode power is the key to enabling near-zero-power sensing nodes at ultra-low data rates.
If the majority of the active elements in such a sensing system can follow this duty-cycling paradigm, then the average power consumption of the system is not set primarily by the active-mode power, but rather from a combination of active-mode and standby-mode power, with a large percentage coming from standby-mode during deeply duty-cycled operation. For example, sensing of temperature, metabolites, and air quality are but a few examples of applications where sensing front-ends do not require rapid sampling, and therefore can be aggressively duty-cycled into ultra-low-power sleep states. Many emerging sensing applications have underlying physical properties that do not vary rapidly with time. Thus, as Bell’s law continues to march on and device sizes continue to scale, it will become necessary to create advances in energy harvesting and near-zero-power electronics in order to overcome limited battery capacities to push into the next generation of ubiquitous sensors and “internet of everything” devices.
Although the power consumption and computational performance of such electronic devices have also scaled with Moore’s law, the battery technology necessary to power portable devices has not scaled nearly as rapidly. The ongoing miniaturization of electronics, as modeled by Bell’s law, has taken solid-state computing platforms from stationary room-sized mainframes to portable platforms such as laptops, smartphones, and smart watches.